{"id":"W4368368735","doi":"10.1002/cjce.24940","title":"Multi‐stage fusion regression network for quality prediction of batch process","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Gansu Education Department; National Natural Science Foundation of China","keywords":"Process (computing); Computer science; Quality (philosophy); Cluster analysis; Autoencoder; Regression; Batch processing; Data mining; Artificial neural network; Artificial intelligence; Stage (stratigraphy); Regression analysis; Machine learning; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001045771,0.000938449,0.0007061074,0.0006472273,0.0003461754,0.0005714126,0.0008534925,0.0008044898,0.000986354],"category_scores_gemma":[0.001310041,0.0004600405,0.0009798076,0.000535163,0.0003085048,0.000958938,0.0004901306,0.001006018,0.0002551852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009307358,"about_ca_system_score_gemma":0.0006792801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01389623,"about_ca_topic_score_gemma":0.007805697,"domain_scores_codex":[0.9995611,0.00006037292,0.00002515417,0.0001659127,0.0001319496,0.00005556141],"domain_scores_gemma":[0.9994937,0.0001616198,0.00006130349,0.00003059805,0.0002348105,0.00001781534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002428278,0.0001240428,0.003265491,0.00007126555,0.0001137628,0.00008857155,0.00006071866,0.854916,0.01914845,0.0008818583,0.0007791811,0.1203079],"study_design_scores_gemma":[0.000001513602,0.00001254321,0.0003020643,0.000001147218,0.000005827402,0.000002940125,0.000001368472,0.9985175,0.001020784,0.00009749941,0.00003433012,0.000002511807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1319194,0.0006685273,0.8636718,0.0001887199,0.00007818116,0.00005764365,0.0001453593,0.001486804,0.001783622],"genre_scores_gemma":[0.9444085,0.000202802,0.05322381,0.00005123145,0.00002739383,0.00005151561,0.0002035485,0.00003979501,0.001791361],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01389623,"threshold_uncertainty_score":0.02763069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221314990042814,"score_gpt":0.2516430697411932,"score_spread":0.2294299198407651,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}